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IEEE Transactions on Medical Imaging is a peer-reviewed journal published by IEEE, covering Medical Imaging Techniques and Applications, Advanced MRI Techniques and Applications, Medical Image Segmentation Techniques. Over its lifetime it has published 8,745 papers, which have received 644,223 citations.
| Publisher | IEEE |
|---|---|
| Reference style | Numbered (IEEE) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, and C. Lee, "A representative article title," IEEE Transactions on Medical Imaging, vol. 12, no. 3, pp. 45–58, 2023.
Formats any DOI in IEEE Transactions on Medical Imaging style. No sign-up. |
| Publishes research in | Medical Imaging Techniques and Applications Advanced MRI Techniques and Applications Medical Image Segmentation Techniques Radiomics and Machine Learning in Medical Imaging Advanced X-ray and CT Imaging |
| ISSN | 0278-0062 |
| Citation impact (2-yr) | 8.26 |
| h-index | 324 |
| i10-index | 5,810 |
| Top institutions publishing here | Harvard University |
| Journal website | ieeexplore.ieee.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogram-based model, the FM has an intrinsic limitation--no spatial information is taken into account. This causes…
In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences. Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low- and high-grade glioma patients-manually annotated by up to four raters-and…
A variant of the popular nonparametric nonuniform intensity normalization (N3) algorithm is proposed for bias field correction. Given the superb performance of N3 and its public availability, it has been the subject of several evaluation studies. These studies have demonstrated the importance of certain parameters associated with the B-spline least-squares fitting. We propose the substitution…
Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs enable learning data-driven, highly representative, hierarchical image features from sufficient training data. However, obtaining datasets as comprehensively annotated as ImageNet in the medical imaging domain remains a challenge. There are currently…
In this paper we present a new approach for the nonrigid registration of contrast-enhanced breast MRI. A hierarchical transformation model of the motion of the breast has been developed. The global motion of the breast is modeled by an affine transformation while the local breast motion is described by a free-form deformation (FFD) based on…
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